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Review Topical Sections

Industrial production, application, microbial biosynthesis and degradation of furanic compound, hydroxymethylfurfural (HMF)

  • Biorefinery is increasingly embraced as an environmentally friendly approach that has the potential to shift current petroleum-based chemical and material manufacture to renewable sources. Furanic compounds, particularly hydroxymethylfurfurals (HMFs) are platform chemicals, from which a variety of value-added chemicals can be derived. Their biomanufacture and biodegradation therefore will have a large impact. Here, we first review the potential industrial production of 4-HMF and 5-HMF, then we summarize the known microbial biosynthesis and biodegradation pathways of furanic compounds with emphasis on the enzymes in each pathway. We especially focus on the structure, function and catalytic mechanism of MfnB (4-(hydroxymethyl)-2-furancarboxyaldehyde-phosphate synthase) and hmfH (HMF oxidase), which catalyze the formation of phosphorylated 4-HMF and the oxidation of 5-HMF to furandicarboxylic acid (2,5-FDCA), respectively. Understanding the structure-function relationship of these enzymes will provide important insights in enzyme engineering, which eventually will find industry applications in mass-production of biobased polymers and other bulk chemicals in future.

    Citation: Yu Wang, Caroline A. Brown, Rachel Chen. Industrial production, application, microbial biosynthesis and degradation of furanic compound, hydroxymethylfurfural (HMF)[J]. AIMS Microbiology, 2018, 4(2): 261-273. doi: 10.3934/microbiol.2018.2.261

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  • Biorefinery is increasingly embraced as an environmentally friendly approach that has the potential to shift current petroleum-based chemical and material manufacture to renewable sources. Furanic compounds, particularly hydroxymethylfurfurals (HMFs) are platform chemicals, from which a variety of value-added chemicals can be derived. Their biomanufacture and biodegradation therefore will have a large impact. Here, we first review the potential industrial production of 4-HMF and 5-HMF, then we summarize the known microbial biosynthesis and biodegradation pathways of furanic compounds with emphasis on the enzymes in each pathway. We especially focus on the structure, function and catalytic mechanism of MfnB (4-(hydroxymethyl)-2-furancarboxyaldehyde-phosphate synthase) and hmfH (HMF oxidase), which catalyze the formation of phosphorylated 4-HMF and the oxidation of 5-HMF to furandicarboxylic acid (2,5-FDCA), respectively. Understanding the structure-function relationship of these enzymes will provide important insights in enzyme engineering, which eventually will find industry applications in mass-production of biobased polymers and other bulk chemicals in future.


    It has been known that organic nutrients (e.g., nitrogen and phosphorus), light, and inorganic carbon are the important factors that affect the growth of phytoplankton. However, previous competition theory only focused on the interaction between the species and nutrients/light (see, e.g., [7,9]), and neglected the role of inorganic carbon. This is probably due to the complexities including the biochemistry of carbon acquisition by phytoplankton and the geochemistry of inorganic carbon in the ecosystem [10,20]. In the Supplementary Information of [20], the authors proposed a system of ODEs modeling the competition of the species for inorganic carbon and light in a well-mixed water column. Dissolved CO2 and carbonic acid are regarded as one resource (denoted as "CO2"), and bicarbonate and carbonate ions are regarded as another (denoted as "CARB"). The resources "CO2" and "CARB" are stored internally, and they are substitutable in their effects on algal growth [17,20]. On the other hand, uptake rates also includes self-shading by the phytoplankton population, namely, an increase in population density will reduce light available for photosynthesis, and thereby suppressing further carbon assimilation and population growth [20].

    It was known that pH and alkalinity are two main factors in the modeling of inorganic carbon [20]. The consumption terms for "CO2" and "CARB" used in [20] include computations of feedbacks that arise from changes in pH and alkalinity during algal growth. In the recent work [17], the authors ignore these latter feedbacks and assume that the parameters in the system are constants, simplifying the complex processes of "CO2" and "CARB" involved. Incorporating the simplifications used in [17], we modify the model presented in the Supplementary Information of [20] and we shall investigate the following chemostat-type model with internal storage:

    $ {dRdt=(R(0)R)DfR1(R,Q1)g1(u1,u2)u1fR2(R,Q2)g2(u1,u2)u2                    +γ1(Q1)u1+γ2(Q2)u2ωrR+ωsS,dSdt=(S(0)S)DfS1(S,Q1)g1(u1,u2)u1fS2(S,Q2)g2(u1,u2)u2+ωrRωsS,dQ1dt=fR1(R,Q1)g1(u1,u2)+fS1(S,Q1)g1(u1,u2)μ1(Q1)Q1γ1(Q1),du1dt=[μ1(Q1)D]u1,dQ2dt=fR2(R,Q2)g2(u1,u2)+fS2(S,Q2)g2(u1,u2)μ2(Q2)Q2γ2(Q2),du2dt=[μ2(Q2)D]u2,R(0)0, S(0)0, ui(0)0, Qi(0)Qmin,i, i=1,2. $ (1.1)

    Here $R(t)$ and $S(t)$ denote the concentrations of "CO2" and "CARB" in the chemostat at time $t$, respectively. $u_{i} (t)$ denotes the concentration of species $i$ at time $t$. $Q_{i}$ represents the amount of cell quota of resources $R$ and $S$ per individual of species $i$ at time $t$. $\mu_{i}(Q_{i})$ is the growth rates of species $i$ as a function of cell quota $Q_{i}$. $f_{Ri}(R, Q_{i})$ ($f_{Si}(S, Q_{i})$) is the per capita uptake rate of species $i$ as a function of resource concentration $R$ ($S$) and cell quota $Q_{i}$. $D$ is the dilution rate of the chemostat. Each nutrient is supplied at the rate $D$, and both input concentrations are $R^{(0)}$ and $S^{(0)}$ respectively. $Q_{\min, i}$ denotes threshold cell quota below which no growth of species $i$ occurs. $\gamma_i(Q_i)$ represents the respiration rate of species $i$ as a function of cell quota $Q_{i}$. $g_i(u_1, u_2)$ stands for the photosynthetic rate of the species $i$ as a function of $u_{1} (t)$ and $u_{2} (t)$. Following the ideas of model simplifications in [17], we also assume that carbonic acid loses a proton to become bicarbonate at the rate $\omega_r$, and the rate of the reverse reaction is denoted by $\omega_s$.

    One type of the photosynthetic rate of the species $i$, $g_i(u_1, u_2)$, takes

    $ gi(u1,u2)=1zmzm0miˆI(z)ai+ˆI(z)dz, $ (1.2)

    where $m_i$ and $a_i$ are the maximal growth rate and half saturation constant of species $i$, respectively, and

    $ ˆI(z)=Iinexp(k0zk1zu1(t)k2zu2(t)). $ (1.3)

    Here we have assumed that the light intensity at each depth is described by Lambert-Beer law [11,14], which states that the amount of light absorbed is proportional to the light intensity ($I_{\rm in}$), but decreases with the depth in the water column ($z$), the background turbidity of the water itself ($k_0$), the specific light attenuation coefficients of the competing species ($k_i$), and the population densities of the species ($u_i$). Assume that $z_m$ is the total depth of the water column. Substituting (1.3) into (1.2), then the photosynthetic rate $g_i(u_1, u_2)$ becomes

    $ gi(u1,u2)=mi(k0+k1u1+k2u2)zmln(ai+Iinai+ˆI(zm))=miln(IinˆI(zm))ln(ai+Iinai+ˆI(zm)), $

    where

    $ ˆI(zm)=Iinexp(k0zmk1zmu1(t)k2zmu2(t)). $

    We also note that the other type of the photosynthetic rate $g_i(u_1, u_2)$ takes the form

    $ gi(u1,u2)=miIai+I, $ (1.4)

    with

    $ I(t)=Iinexp(k0zmk1zmu1(t)k2zmu2(t)). $

    According to [20], we take the growth rate $\mu_{i}(Q_{ i})$ as follows

    $ μi(Qi)=μmax,iQiQmin,iQmax,iQmin,i, $

    where $\mu_{\max, i}$ is the maximum specific growth rate of species $i$; $Q_{\min, i}$ is the minimum cellular carbon content required for growth of species $i$; $Q_{\max, i}$ is the maximum cellular carbon content of species $i$. From [3,4,5], for $i = 1, 2$, the growth rate $\mu_{i}(Q_{ i})$ can also take the forms :

    $ μi(Qi)=μ,i(1Qmin,iQi),orμi(Qi)=μ,i(QiQmin,i)+Ai+(QiQmin,i)+, $

    where $(Q_{ i}-Q_{\min, i})_+$ is the positive part of $(Q_{ i}-Q_{\min, i})$ and $\mu_{\infty, i}$ is the maximal growth rate at infinite quotas (i.e., as $Q_{ i} \rightarrow \infty$) of the species $i$.

    According to [6,16], for $H = R, \ S$ and $i = 1, 2$, the uptake rate $f_{H i}(H, Q_{i})$ takes the form:

    $ fHi(H,Qi)=ρHi(Qi)HKHi+H. $

    Here $H = R, \ S$ represents the concentration of the extracellular resource; $\rho_{H i}(Q_{ i})$ represents the maximal uptake rate of the species $i$; $K_{H i}$ is the half-saturation constant, the resource concentration at which uptake rate is half of the maximal rate. The maximal resource uptake rate, $\rho_{H i}(Q_{ i})$, is a decreasing, linear function of quota [8,16], which is defined by

    $ ρHi(Qi)=ρhighmax,Hi(ρhighmax,Hiρlowmax,Hi)QiQmin,iQmax,iQmin,i, $

    for $Q_{\min, i}\leq Q_{ i}\leq Q_{\max, i}$. In other words, the maximal rate of resource uptake, $\rho_{H i}(Q_{ i})$, varies between upper and lower bounds, $\rho_{\max, H i}^{\rm high}$ and $\rho_{\max, H i}^{\rm low}$, respectively, while quota varies between lower and upper bounds, $Q_{\min, i}$ and $Q_{\max, i}$, respectively (see, e.g., [8]). Cunningham and Nisbet [1,2] took $\rho_{H i}(Q_{ i})$ to be a constant. The authors in [20] put $\rho_{\max, H i}^{\rm high}\equiv\rho_{\max, H i}$, $\rho_{\max, H i}^{\rm low} = 0$, then $\rho_{H i}(Q_{ i})$ becomes

    $ ρHi(Qi)=ρmax,HiQmax,iQiQmax,iQmin,i. $

    System (1.1) also includes the fact that carbon is lost by respiration. The respiration rate is proportional to the size of the transient carbon pool [20]:

    $ γi(Qi)=γmax,iQiQmin,iQmax,iQmin,i, $

    where $Q_{\min, i}\leq Q_{ i}\leq Q_{\max, i}$, and $\gamma_{\max, i}$ is the maximum respiration rate of species $i$.

    In this whole paper, we always assume that the photosynthetic rate $g_i(u_1, u_2)$ takes the form in (1.2) or (1.4); the functions $\mu_{ i}(Q_{ i})$, $f_{H i}(H, Q_{ i})$, and $\gamma_{i}(Q_{ i})$ satisfy the following assumptions: ($i = 1, 2$ and $H = R, \ S$)

    $\rm(C1)$ $\mu_{ i}(Q_{i})$ is continuously differentiable for $Q_{ i}\ge Q_{\min, i}$, $ \mu_{ i}(Q_{\min, i}) = 0$, $\mu_{ i}(Q_{ i})\geq0$ and $\mu_{ i}'(Q_{ i})>0$ for $Q_{ i}\ge Q_{\min, i}$.

    $\rm(C2)$ $f_{H i}(H, Q_{ i})$ is continuously differentiable for $H>0$ and $Q_{ i}\ge Q_{\min, i}$, $f_{H i}(0, Q_{i}) = 0$, $f_{H i}(H, Q_{i})\ge 0$, $ \frac{\partial f_{H i}(H, Q_{i})}{\partial H}>0$ and $\frac{\partial f_{H i}(H, Q_{ i})}{\partial Q_{ i}}\leq 0$ for $H>0$ and $Q_{ i}\ge Q_{\min, i}$.

    $\rm(C3)$ $\gamma_{i}(Q_{i})$ is continuously differentiable for $Q_{ i}\ge Q_{\min, i}$, $ \gamma_{i}(Q_{\min, i}) = 0$, $\gamma_{i}(Q_{ i})\geq0$ and $\gamma_{i}'(Q_{ i})>0$ for $Q_{ i}\ge Q_{\min, i}$.

    The rest of the paper is organized as follows. Section 2 is devoted to the study of the single population model. In Section 3, we shall investigate the possibility of coexistence of the two competing species system (1.1). A brief discussion section completes this paper.

    In this section, we first investigate the extinction and persistence of the single population model. Mathematically, it simply means that we remove equations of $Q_2$ and $u_2$ from (1.1). In order to simplify notation, all subscripts are dropped in the remaining equations and the single population model takes the form:

    $ {dRdt=(R(0)R)DfR(R,Q)G(u)u+γ(Q)uωrR+ωsS,dSdt=(S(0)S)DfS(S,Q)G(u)u+ωrRωsS,dQdt=fR(R,Q)G(u)+fS(S,Q)G(u)μ(Q)Qγ(Q),dudt=[μ(Q)D]u,R(0)0, S(0)0, u(0)0, Q(0)Qmin. $ (2.1)

    The specific growth rate $G(u)$ takes the form

    $ G(u)=1zmzm0m˜I(z)a+˜I(z)dz=mln(Iin˜I(zm))ln(a+Iina+˜I(zm)), $

    where

    $ ˜I(z)=Iinexp(k0zkzu(t)), 0zzm, $

    or

    $ G(u)=mIa+I, with I(t)=Iinexp(k0zmkzmu(t)). $

    The feasible domain for system (2.1) takes the form

    $ X={(R,S,Q,u)R4+:QQmin}. $ (2.2)

    Then it is easy to show that $\mathbf{X}$ is positively invariant for system (2.1). Next, we study the boundedness of solutions of (2.1):

    Lemma 2.1. Every solution $(R(t), S(t), Q(t), u(t))$ of system (2.1) exists globally. Furthermore, solutions of (2.1) are ultimately bounded on $\mathbf{X}$.

    Proof. By the continuation theorem, it suffices to prove that the solution of system (2.1) is bounded on finite time intervals. Let

    $ Θ(t)=R(t)+S(t)+u(t)Q(t). $ (2.3)

    Then $\Theta(t)$ satisfies

    $ dΘ(t)dt=(R(0)+S(0)Θ(t))D. $ (2.4)

    Thus, $\Theta(t)$ is bounded on finite time intervals. This fact and the positivity of the solution imply that $R(t)$, $S(t)$, and $u(t)Q(t)$ are bounded on finite time intervals. Since $Q(t)\geq Q_{\min}$, we can also deduce that $u(t)$ is bounded on finite time intervals.

    It remains to show that $Q(t)$ is bounded on finite time intervals. Inspired by the ideas in [15,Proposition 3], we will investigate the dynamics of the variable $V(t) = \frac{1}{2}(Q(t))^2$. By the monotonicity of $f_{N}$ for $N = S, R$, the inequality $x\leq \frac 12(1+x^2)$, and the fact that $Q \ge Q_{\min}$, it is easy to see that $V(t)$ satisfies

    $ dV(t)dt=dQ(t)dtQG(0)[fR(R(t),Qmin)+fS(S(t),Qmin)]Q12G(0)[fR(R(t),Qmin)+fS(S(t),Qmin)][1+Q2]=G(0)[fR(R(t),Qmin)+fS(S(t),Qmin)][12+V]. $ (2.5)

    Since $R(t)$ and $S(t)$ in (2.5) are bounded on finite time intervals, we see that $V(t)$ is bounded on finite time intervals, and hence, so is $Q(t)$. Thus, every solution of system (2.1) exists globally.

    From (2.4), it is easy to see that

    $ limtΘ(t)=R(0)+S(0), $ (2.6)

    and hence, $\Theta(t)$ is ultimately bounded. This together with the positivity of the solution, we deduce that $R(t)$, $S(t)$, and $u(t)Q(t)$ are ultimately bounded. Using the fact $Q(t)\geq Q_{\min}$, we see that $u(t)$ is ultimately bounded. Finally, we show that $Q(t)$ is ultimately bounded. From (2.3), (2.6), and the third equation of (2.1), it follows that there exist $\tau_0>0$ and $\eta_0>0$ such that

    $ \frac{d Q}{dt}\leq G(0)[f_{R}(R^{(0)}+S^{(0)}, Q)+f_{S}(R^{(0)}+S^{(0)}, Q)]+\eta_0-\mu(Q)Q-\gamma(Q), \ t\geq \tau_0. $

    Then

    $ \lim\limits_{t\rightarrow \infty}Q(t)\leq Q^{\eta_0}, $

    where $Q^{\eta_0}$ is the positive root uniquely determined by

    $ G(0)[f_{R}(R^{(0)}+S^{(0)}, Q)+f_{S}(R^{(0)}+S^{(0)}, Q)]+\eta_0-\mu(Q)Q-\gamma(Q) = 0. $

    Thus, solutions of (2.1) are ultimately bounded on $\mathbf{X}$ since $\eta_0>0$ is independent of initial values.

    In order to find the species-free equilibrium of system (2.1), which corresponds to the absence of species, we put $u = 0$ in (2.1). Then we consider the following system

    $ {dRdt=(R(0)R)DωrR+ωsS,dSdt=(S(0)S)D+ωrRωsS,R(0)0, S(0)0. $ (2.7)

    It is easy to see that (2.7) is a cooperative/monotone system (see, e.g., [18]), and

    $ (R^{*}, S^{*}): = (\frac{DR^{(0)}+\omega_sR^{(0)}+\omega_sS^{(0)}}{D+\omega_r+\omega_s}, \frac{DS^{(0)}+\omega_rS^{(0)}+\omega_rR^{(0)}}{D+\omega_r+\omega_s}) $

    is the unique equilibrium for (2.7). For a monotone dynamical system, the unique steady state is globally asymptotically stable if and only if every forward orbit has compact closure (see [13,Theorem D]). By Lemma 2.1 and the above discussions, we have the following results:

    Lemma 2.2. The unique equilibrium $(R^{*}, S^{*})$ is globally asymptotically stable for (2.7) in $\mathbb{R}^2$.

    From Lemma 2.2, the species-free equilibrium of system (2.1), which we label $E_0$, is given by

    $ E_0 = (R, S, Q, u) = (R^{*}, S^{*}, Q^{*}, 0), $

    where $Q^{*}$ satisfies

    $ fR(R,Q)G(0)+fS(S,Q)G(0)μ(Q)Qγ(Q)=0 $ (2.8)

    The local stability of $E_0$ is determined by the Jacobian matrix of (2.1) at $E_0$, denoted by

    $ J0=(Dωrωs0fR(R,Q)G(0)+γ(Q)ωrDωs0fS(S,Q)G(0)fR(R,Q)RG(0)fS(S,Q)SG(0)j33[fR(R,Q)+fS(S,Q)]G(0)000μ(Q)D), $

    where

    $ j33=[fR(R,Q)Q+fS(S,Q)Q]G(0)[μ(Q)+μ(Q)Q]γ(Q)<0. $

    It is easy to see that the eigenvalues of $J_0$ are $j_{33}$, $\mu(Q^{*})-D$, together with the eigenvalues of the following matrix

    $ ˜J0=(DωrωsωrDωs). $

    Since $j_{33}<0$ and the eigenvalues of $\tilde{J}_0$ are both negative, we see that the sign of $\mu(Q^{*})-D$ determines the stability of $E_0$. That is, $E_0$ is locally asymptotically stable if $\mu(Q^{*})-D<0$, and unstable if $\mu(Q^{*})-D>0$. Thus, we have proved the following result concerning with the local stability of $E_0$:

    Lemma 2.3. $E_0$ is locally asymptotically stable if $\mu(Q^{*})-D<0$, and unstable if $\mu(Q^{*})-D>0$.

    This subsection is devoted to the investigations of persistence of system (2.1).

    Theorem 2.4. Assume that $(R(t), S(t), Q(t), u(t))$ is the unique nonnegative solution of system (2.1), for all $t\in[0, \infty)$, with the initial value $(R^0, S^0, Q^0, u^0)\in \mathbf{X}$. If $\mu(Q^{*})-D>0$, then system (2.1) is uniformly persistent in the sense that there exists a $\xi>0$ such that

    $ \liminf\limits_{t\rightarrow\infty}u(t)\geq \xi, \ provided~ that\ u^0\neq 0. $

    Further, system (2.1) admits at least one positive equilibrium $(\hat{R}, \hat{S}, \hat{Q}, \hat{u})$.

    Proof. Recall that $\mathbf{X}$ is defined in (2.2). Let

    $ X0={(R,S,Q,u)X:u>0}, $

    and

    $ X0:=XX0:={(R,S,Q,u)X:u=0}. $

    It is easy to see that both $\mathbf{X}$ and $\mathbf{X}_0$ are positively invariant for system (2.1), and $\partial \mathbf{X}_0$ is relatively closed in $\mathbf{X}$. Furthermore, system (2.1) is point dissipative (see Lemma 2.1). Let $\Phi(t):\mathbf{X}\rightarrow \mathbf{X}$ be the solution maps associated with system (2.1). Set $\tilde{M}_\partial: = \{P\in \partial\mathbf{X}_0: \Phi(t)P\in \partial\mathbf{X}_0, \ \forall \ t\geq0\}$ and $\tilde{\omega}(P)$ be the omega limit set of the orbit $\tilde{O}^{+}(P): = \{\Phi(t)P:t\geq 0\}$. We show the following claim.

    Claim: $\tilde{\omega}(P) = \{E_0\}, \ \forall \ P\in \tilde{M}_{\partial}$.

    Since $P\in \tilde{M}_{\partial}$, we have $\Phi(t)P\in \partial\mathbf{X}_0, \ \forall \ t\geq 0$. Thus, $u(t, P) = 0, \ \forall \ t\geq 0.$ In view of the first two equations of (2.1), it follows that $(R(t, P), S(t, P))$ satisfies (2.7), $\forall \ t\geq 0$. Then Lemma 2.2 implies that

    $ \lim\limits_{t\rightarrow \infty}(R(t, P), S(t, P)) = (R^{*}, S^{*}). $

    Then, the equation for $Q(t)$ in (2.1) is asymptotic to

    $ \frac{dQ}{dt} = f_{R}(R, Q)G(0)+f_{S}(S, Q)G(0)-\mu(Q)Q-\gamma(Q). $

    From the theory for asymptotically autonomous semiflows (see, e.g., [19,Corollary 4.3]), it follows that $\lim_{t\rightarrow \infty}Q(t, P) = Q^{*}$, where $Q^{*}$ is given in (2.8). Hence, the claim is proved.

    Let $\eta_1: = \frac{1}{2}\left(\mu(Q^{*})-D\right)>0$. Then it follows from the continuity of $\mu(Q)$ that there exists $\sigma_1>0$ such that

    $ μ(Q)>μ(Q)η1,  |QQ|<σ1. $ (2.9)

    Claim: $E_0$ is a uniform weak repeller for $\mathbf{X}_0$ in the sense that

    $ lim supt|Φt(P)E0|σ1,  PX0. $

    Suppose not. Then there exists a $P\in \mathbf{X}_0$ such that

    $ \limsup\limits_{t\rightarrow\infty}|\Phi_t(P)-E_0| \lt \sigma_1. $

    Thus, there exists a $\tau_1>0$ such that

    $ |Q(t, P)-Q^{*}| \lt \sigma_1, \ \forall \ t\geq \tau_1. $

    This and (2.9) imply that

    $ \mu(Q(t, P))-D \gt \mu(Q^{*})-D-\eta_1 = \eta_1, \ \forall \ t\geq \tau_1. $

    From this inequality and the fourth equation of (2.1), we have

    $ du(t,P)dt>η1u(t,P),  tτ1, $

    which shows that $\lim_{t\rightarrow\infty}u(t, P) = \infty$, a contradiction.

    Therefore, $E_0$ is isolated in $\mathbf{X}$ and $\tilde{W}^s(E_0)\cap \mathbf{X}_{0} = \emptyset$, where $\tilde{W}^{s}(E_0)$ is the stable set of $E_0$ (see [21]). Since $\Phi_t:\mathbf{X} \rightarrow \mathbf{X}$ is point dissipative and compact, we conclude from [21,Theorem 1.1.3] that there exists a global attractor $\mathcal{A}$ for $\Phi_t$ in $\mathbf{X}$. By [21,Theorem 1.3.1] on strong repellers, $\Phi_t:\mathbf{X} \rightarrow \mathbf{X}$ is uniformly persistent with respect to $(\mathbf{X}_0, \partial\mathbf{X}_0)$. It follows from [21,Theorem 1.3.6] that there exists a global attractor $\mathcal{A}_0$ for $\Phi_t$ in $\mathbf{X}_0$ and $\Phi_t$ admits at least one fixed point

    $ (\hat{R}, \hat{S}, \hat{Q}, \hat{u})\in \mathbf{X}_0. $

    Then $\hat{Q}\geq Q_{\min}>0$, $\hat{u}>0$, and $(\hat{R}, \hat{S})$ satisfies

    $ {(R(0)ˆR)DfR(ˆR,ˆQ)g(ˆu)ˆu+γ(ˆQ)ˆuωrˆR+ωsˆS=0,(S(0)ˆS)DfS(ˆS,ˆQ)g(ˆu)ˆu+ωrˆRωsˆS=0. $ (2.10)

    In view of (2.10), we deduce that $\hat{R}>0, \ \hat{S}>0$. Thus, $(\hat{R}, \hat{S}, \hat{Q}, \hat{u})$ is a positive steady-state solution for (2.1). We complete the proof.

    In this subsection, we neglect the effect of respiration and investigate the extinction of system (2.1). Putting the respiration rate to be zero,

    $ γ(Q)0,  QQmin. $ (2.11)

    Then we have the following result:

    Theorem 2.5. Suppose $(R(t), S(t), Q(t), u(t))$ is the unique nonnegative solution of system (2.1), for all $t\in[0, \infty)$, with the initial value $(R^0, S^0, Q^0, u^0)\in \mathbf{X}$. Assume that (2.11) holds. If $\mu(Q^{*})-D<0$, then system (2.1) is washed out, that is,

    $ limt(R(t),S(t),Q(t),u(t))=(R,S,Q,0). $

    Proof. For $\eta>0$, we assume that $Q^{\eta}$ is the unique root of

    $ G(0)[fR(R,Q)+fS(S,Q)]+ημ(Q)Q=0. $ (2.12)

    Recall that $Q^{*}$ is the unique root of (2.8). Since

    $ \lim\limits_{\eta\rightarrow 0}[\mu(Q^{\eta})-D] = \mu(Q^{*})-D\ \mbox{and}\ \frac{-1}{3}[\mu(Q^{*})-D] \gt 0, $

    we may find an $\eta_2>0$ such that

    $ μ(Qη2)D<[μ(Q)D]+13[μ(Q)D]=23[μ(Q)D]. $ (2.13)

    On the other hand, by the continuity, we may find a $\sigma_2>0$ such that

    $ {fR(R+σ2,Q)<fR(R,Q)+η22G(0),fS(S+σ2,Q)<fS(S,Q)+η22G(0),μ(Qη2+σ2)<μ(Qη2)+13[μ(Q)D] $ (2.14)

    In view of the assumption (2.11) and the first two equations of system (2.1), it follows that

    $ {dRdt(R(0)R)DωrR+ωsS,dSdt(S(0)S)D+ωrRωsS. $

    By the comparison arguments and Lemma 2.2, we have

    $ \lim\limits_{t\rightarrow \infty}(R(t), S(t))\leq (R^{*}, S^{*}). $

    Then there exists a $\tau_2>0$ such that

    $ R(t)R+σ2, S(t)S+σ2,  tτ2. $

    Then it follows from the third equation of (2.1) that

    $ dQdtG(0)[fR(R+σ2,Q)+fS(S+σ2,Q)]μ(Q)Q,  tτ2. $ (2.15)

    In view of the first two inequalities of (2.14) and (2.15), we have

    $ dQdtG(0)[fR(R,Q)+fS(S,Q)]+η2μ(Q)Q,  tτ2. $

    Using the comparison arguments, we have

    $ limtQ(t)Qη2, $ (2.16)

    where $Q^{\eta_2}$ is the unique root of (2.12) with $\eta = \eta_2$. Thus, we may find a $\tau_3>0$ such that

    $ Q(t)Qη2+σ2,  tτ3, $

    and hence,

    $ μ(Q(t))μ(Qη2+σ2),  tτ3. $ (2.17)

    In view of the third inequality of (2.14) and (2.17), we have

    $ μ(Q(t))μ(Qη2)+13[μ(Q)D],  tτ3. $ (2.18)

    By (2.13), (2.18) together with the fourth equation of (2.1), it follows that

    $ dudt=[μ(Q(t))D]u13[μ(Q)D]u,  tτ3. $ (2.19)

    Since $\mu(Q^{*})-D<0$ and (2.19), we have

    $ limtu(t)=0. $

    Then $(R(t), S(t))$ is asymptotic to (2.7). By Lemma 2.2 and the theory for asymptotically autonomous semiflows (see, e.g., [19,Corollary 4.3]), it follows that

    $ \lim\limits_{t\rightarrow \infty}(R(t), S(t)) = (R^{*}, S^{*}). $

    Similarly, $Q(t)$ is asymptotic to

    $ \frac{dQ}{dt} = f_{R}(R^{*}, Q)G(0)+f_{S}(S^{*}, Q)G(0)-\mu(Q)Q, $

    and $\lim_{t\rightarrow \infty}Q(t) = Q^{*}$, where $Q^{*}$ is given in (2.8) with $\gamma(Q)\equiv 0$. We complete the proof.

    In this section, we shall concentrate on the study of coexistence of system (1.1). The subsequent discussions will reveal that two semi-trivial steady-state solutions of system (1.1), corresponds to the presence of one of the species and the absence of the other species, are not necessarily unique. This makes our analysis more difficult. Fortunately, we can adopt the ideas developed in [12,Section 4] to overcome this difficulty.

    The trivial steady-state solution of (1.1), labeled $\mathcal{E}_0$, corresponds to the absence of both species. It is given by

    $ \mathcal{E}_0 = (R, S, Q_1, u_1, Q_2, u_2) = (R^{*}, S^{*}, Q_1^{*}, 0, Q_2^{*}, 0), $

    where $(R^{*}, S^{*})$ is given in Lemma 2.2, and $Q_i^{*}$ satisfies

    $ fRi(R,Qi)Gi(0)+fSi(S,Qi)Gi(0)μi(Qi)Qiγi(Qi)=0, i=1,2, $

    where $G_1(u_1) = g_1(u_1, 0)$ and $G_2(u_2) = g_2(0, u_2)$.

    In order to determine the semi-trivial steady-state solutions of (1.1), we need the following single population system associated with the growth of species $i$:

    $ {dRdt=(R(0)R)DfRi(R,Qi)Gi(ui)ui+γi(Qi)uiωrR+ωsS,dSdt=(S(0)S)DfSi(S,Qi)Gi(ui)ui+ωrRωsS,dQidt=fRi(R,Qi)Gi(ui)+fSi(S,Qi)Gi(ui)μi(Qi)Qiγi(Qi),duidt=[μi(Qi)D]ui,R(0)0, S(0)0, ui(0)0, Qi(0)Qmin,i, i=1,2. $ (3.1)

    Next, we shall summarize the result of system (3.1). By Theorem 2.4, for $i = 1, 2$, system (3.1) admits at least one positive equilibrium and we may assume that $A_i^{0}\subset$$\rm{Int}$$\mathbb{R}_{+}^4$ is a global attractor of the semiflows generated by system (3.1), under the condition that $\mu_i(Q_i^{*})-D>0$. One of the semi-trivial steady-state solutions of (1.1), labeled $\mathcal{E}_1$, corresponds to the presence of species 1 and the absence of species 2. It is given by

    $ \mathcal{E}_1 = (R, S, Q_1, u_1, Q_2, u_2) = (\hat{R}_1, \hat{S}_1, \hat{Q}_1, \hat{u}_1, \hat{Q}_2, 0), $

    where $(\hat{R}_1, \hat{S}_1, \hat{Q}_1, \hat{u}_1)\in A_1^{0}$ is a positive equilibrium of system (3.1) with $i = 1$, which is not necessarily unique. Here, $\hat{Q}_2 = \hat{Q}_2(\hat{R}_1, \hat{S}_1, \hat{Q}_1, \hat{u}_1)$ is the root of

    $ fR2(ˆR1,Q2)g2(ˆu1,0)+fS2(ˆS1,Q2)g2(ˆu1,0)μ2(Q2)Q2γ2(Q2)=0. $ (3.2)

    Inspired by the arguments in [12,Section 4], we assume that

    $ ˆQmin2=inf{ˆQ2(ˆR1,ˆS1,ˆQ1,ˆu1):(ˆR1,ˆS1,ˆQ1,ˆu1)A01}. $ (3.3)

    The other semi-trivial steady-state solution of (1.1), labeled $\mathcal{E}_2$, corresponds to the presence of species 2 and the absence of species 1. It is given by

    $ \mathcal{E}_2 = (R, S, Q_1, u_1, Q_2, u_2) = (\check{R}_2, \check{S}_2, \check{Q}_1, 0, \check{Q}_2, \check{u}_2), $

    where $(\check{R}_2, \check{S}_2, \check{Q}_2, \check{u}_2)\in A_2^{0}$ is a positive equilibrium of system (3.1) with $i = 2$, which is not necessarily unique. Here, $\check{Q}_1 = \check{Q}_1(\check{R}_2, \check{S}_2, \check{Q}_2, \check{u}_2)$ is the root of

    $ fR1(ˇR2,Q1)g1(0,ˇu2)+fS1(ˇS2,Q1)g1(0,ˇu2)μ1(Q1)Q1γ1(Q1)=0. $

    Similarly, we assume

    $ ˇQmin1=inf{ˇQ1(ˇR2,ˇS2,ˇQ2,ˇu2):(ˇR2,ˇS2,ˇQ2,ˇu2)A02}. $ (3.4)

    The feasible domain for system (1.1) takes the form

    $ Y={(R,S,Q1,u1,Q2,u2)R6+:QQmin,i, i=1,2}. $

    Then it is easy to show that $\mathbf{Y}$ is positively invariant for system (1.1). By the similar arguments in Lemma 2.1, we can show the following result:

    Lemma 3.1. Every solution $(R(t), S(t), Q_1(t), u_1(t), Q_2(t), u_2(t))$ of system (1.1) exists globally. Furthermore, solutions of (1.1) are ultimately bounded on $\mathbf{Y}$.

    Assume that $\Psi(t):\mathbf{Y}\rightarrow\mathbf{Y}$ is the semiflow associated with system (1.1). Let

    $ Y0={(R,S,Q1,u1,Q2,u2)Y:u1>0 and u2>0}, $

    and

    $ Y0:=YY0:={(R,S,Q1,u1,Q2,u2)Y:u1=0 or u2=0}. $

    Following the ideas in [12,Section 4], we assume that $\mathcal{M}_0 = \{\mathcal{E}_0\}$,

    $ M1={(ˆR1,ˆS1,ˆQ1,ˆu1,ˆQ2,0)Y:(ˆR1,ˆS1,ˆQ1,ˆu1)A01 and ˆQ2  is defined by (3.2)}, $

    and

    $ M2={(ˇR2,ˇS2,ˇQ1,0,ˇQ2,ˇu2)Y:(ˇR2,ˇS2,ˇQ2,ˇu2)A02 and ˇQ1  is defined by (3.4)}. $

    One can easily to use "the method of proof by contradiction" to deduce the following result:

    Lemma 3.2. Let $\mu_i(Q_i^{*})-D>0$, for some $i\in \{1, 2\}$. Then $\mathcal{M}_0$ is a uniform weak repeller in the sense that there exists a $\delta_0>0$ such that

    $ lim supt|Ψ(t)v0M0|δ0, for all v0Y0. $

    Next, we shall use the strategy in [12,Lemma 4.2] to show the following result:

    Lemma 3.3. Let $\mu_i(Q_i^{*})-D>0$, for each $i\in \{1, 2\}$. If $\mu_2(\hat{Q}_2^{\min})-D>0$, then $\mathcal{M}_1$ is a uniform weak repeller in the sense that there exists a $\delta_1>0$ such that

    $ lim suptdist(Ψ(t)v0,M1)δ1, for all v0Y0. $ (3.5)

    Proof. Let

    $ B1={ˆQ2=ˆQ2(ˆR1,ˆS1,ˆQ1,ˆu1):(ˆR1,ˆS1,ˆQ1,ˆu1)A01 and ˆQ2  is defined by (3.2)}. $

    Then

    $ \hat{Q}_2^{\min} = \inf\{\hat{Q}_2(\hat{R}_1, \hat{S}_1, \hat{Q}_1, \hat{u}_1):\hat{Q}_2(\hat{R}_1, \hat{S}_1, \hat{Q}_1, \hat{u}_1)\in B_1\}. $

    Setting

    $ \epsilon_1 = \frac{1}{2}[\mu_2(\hat{Q}_2^{\min})-D] \gt 0. $

    Define $\mathcal{G}:B_1\rightarrow \mathbb{R}$ by

    $ \mathcal{G}(\phi) = \mu_2(\phi), \ \phi\in B_1. $

    We may find a $\delta_1>0$ such that

    $ \text{dist}(\mathcal{G}(\phi), \mathcal{G}(B_1)) \lt \epsilon_1, $

    whenever $\phi\in \mathbb{R}$ with $\text{dist}(\phi, B_1)<\delta_1$. Since $B_1$ is compact, it follows that for any $\phi\in \mathbb{R}$ with $\text{dist}(\phi, B_1)<\delta_1$, there exists $\phi_*\in B_1$ with $\phi_*$ depending on $\phi$ such that

    $ |\mathcal{G}(\phi)-\mathcal{G}(\phi_*)| = \text{dist}(\mathcal{G}(\phi), \mathcal{G}(B_1)) \lt \epsilon_1. $

    Thus, we have

    $ |μ2(ϕ)μ2(ϕ)|=|G(ϕ)G(ϕ)|<ϵ1, $

    whenever $\phi\in \mathbb{R}$ with $\text{dist}(\phi, B_1)<\delta_1$.

    Suppose that (3.5) is not true. Then there exists $\mathbf{v}^0\in\mathbf{Y}_0$ such that

    $ lim suptdist(Ψ(t)v0,M1)<δ1. $

    This implies that

    $ lim suptdist(Q2(t),B1)<δ1  and  lim supt|u2(t)|<δ1. $ (3.7)

    From the first inequality of (3.7), we can choose $t_1>0$ such that

    $ dist(Q2(t),B1)<δ1,  tt1. $

    By (3.6), it follows that there exists $\phi_*^t\in B_1$ such that

    $ |μ2(Q2(t))μ2(ϕt)|<ϵ1,  tt1, $

    which implies that

    $ μ2(Q2(t))D>μ2(ϕt)Dϵ1μ2(ˆQmin2)Dϵ1=ϵ1,  tt1. $

    From the sixth equation of (1.1), we have

    $ du2(t)dt=[μ2(Q2(t))D]u2(t)>ϵ1u2(t),  tt1. $

    We deduce that $\lim_{t\rightarrow \infty}u_{2}(t) = \infty$ since $\epsilon_1>0$ and $u_{2}(t_1)>0$. This contradicts the second inequality of (3.7) and we complete the proof.

    By the same arguments in Lemma 3.3, the following result holds:

    Lemma 3.4. Let $\mu_i(Q_i^{*})-D>0$, for each $i\in \{1, 2\}$. If $\mu_1(\check{Q}_1^{\min})-D>0$, then $\mathcal{M}_2$ is a uniform weak repeller in the sense that there exists a $\delta_2>0$ such that

    $ lim suptdist(Ψ(t)v0,M2)δ2, for all v0Y0. $

    Now we are in a position to prove the main result of this paper.

    Theorem 3.5. Assume that $(R(t), S(t), Q_1(t), u_1(t), Q_2(t), u_2(t))$ is the unique solution of (1.1) with the initial value $(R(0), S(0), Q_1(0), u_1(0), Q_2(0), u_2(0))\in \mathbf{Y}$. Let $\mu_i(Q_i^{*})-D>0, \ \forall \ i = 1, 2$, $\mu_2(\hat{Q}_2^{\min})-D>0$, and $\mu_1(\check{Q}_1^{\min})-D>0$. Then system (1.1) is uniformly persistent with respect to $(\mathbf{Y}_0, \partial \mathbf{Y}_0)$ in the sense that there is a positive constant $\zeta>0$ such that if $u_1(0)\neq 0$ and $u_2(0)\neq 0$, we have

    $ lim inftui(t)ζ, i=1,2. $

    Furthermore, system (1.1) admits at least one (componentwise) positive equilibrium.

    Proof. Recall that $\Psi(t):\mathbf{Y}\rightarrow\mathbf{Y}$ is the semiflow associated with system (1.1). It is easy to see that $\Psi(t)\mathbf{Y}_0\subset\mathbf{Y}_0$. Since solutions of the system (1.1) are ultimately bounded (see Lemma 3.1), it follows that $\Psi(t)$ is point dissipative and compact, and hence, $\Psi(t)$ admits a global attractor (see, e.g., [21,Theorem 1.1.3]). Let

    $ M_{\partial}: = \{\mathbf{v}^0 \in \partial \mathbf{Y}_{0}:\Psi(t)\mathbf{v}^0\in \partial \mathbf{Y}_{0}, \forall \ t\geq 0\}, $

    and $\omega(\mathbf{v}^0)$ be the omega limit set of the orbit $O^{+}(\mathbf{v}^0): = \{\Psi(t)\mathbf{v}^0:t\geq 0\}$.

    Claim: $\bigcup_{\mathbf{v}^0\in M_{\partial}}\omega(\mathbf{v}^0)\subset \mathcal{M}_0\cup \mathcal{M}_1 \cup\mathcal{M}_2$.

    For any given $\mathbf{v}^0: = (R^0, S^0, Q_1^0, u_1^0, Q_2^0, u_2^0)\in M_{\partial}$, we have $\mathbf{v}^0\in \partial \mathbf{Y}_{0}$ and $\Psi(t)\mathbf{v}^0\in \partial \mathbf{Y}_{0}, \ \forall \ t\geq 0$. We discuss the following three subcases:

    (ⅰ) If $u_1^0 = 0, \ u_2^0 = 0$, then we have $u_1(t, \mathbf{v}^0) = 0$ and $u_2(t, \mathbf{v}^0) = 0$, $\forall\ t\geq0$. Thus, it is easy to see that $\lim_{t\rightarrow \infty}\Psi(t)\mathbf{v}^0 = \mathcal{E}_0$.

    (ⅱ) If $u_1^0 \neq 0, \ u_2^0 = 0$, then we have $u_1(t, \mathbf{v}^0)> 0$ and $u_2(t, \mathbf{v}^0) = 0$, $\forall\ t\geq0$. Then $(R(t, \mathbf{v}^0), S(t, \mathbf{v}^0), Q_1(t, \mathbf{v}^0), u_1(t, \mathbf{v}^0))$ satisfies system (3.1) with $i = 1$. Since $\mu_1(Q_1^{*})-D>0$, it follows from Theorem 2.4 that

    $ (R(t, \mathbf{v}^0), S(t, \mathbf{v}^0), Q_1(t, \mathbf{v}^0), u_1(t, \mathbf{v}^0)) $

    will eventually enter the global attractor $A_1^{0}\subset$$\rm{Int}$$\mathbb{R}_{+}^4$, and hence, $\Psi(t)\mathbf{v}^0$ will eventually enter $\mathcal{M}_1$.

    (ⅲ) If $u_1^0 = 0, \ u_2^0\neq 0$, then we have $u_1(t, \mathbf{v}^0) = 0$ and $u_2(t, \mathbf{v}^0)> 0$, $\forall\ t\geq0$. Then $(R(t, \mathbf{v}^0), S(t, \mathbf{v}^0), Q_2(t, \mathbf{v}^0), u_2(t, \mathbf{v}^0))$ satisfies system (3.1) with $i = 2$. Since $\mu_2(Q_2^{*})-D>0$, it follows from Theorem 2.4 that

    $ (R(t, \mathbf{v}^0), S(t, \mathbf{v}^0), Q_2(t, \mathbf{v}^0), u_2(t, \mathbf{v}^0)) $

    will eventually enter the global attractor $A_2^{0}\subset$$\rm{Int}$$\mathbb{R}_{+}^4$, and hence, $\Psi(t)\mathbf{v}^0$ will eventually enter $\mathcal{M}_2$.

    The proof of the claim is complete.

    By Lemma 3.2, Lemma 3.3 and Lemma 3.4, it follows that for $i = 0, 1, 2$, $\mathcal{M}_i$ is a uniform weak repeller for $\mathbf{Y}_{0}$ in the sense that there exists $\delta_i>0$ such that

    $ lim suptdist(Ψ(t)v0,Mi)δi, for all v0Y0. $

    Note that $\mathcal{M}_0$, $\mathcal{M}_1$, and $\mathcal{M}_2$ are pairwise disjoint, compact and isolated invariant sets for $\Psi(t)$ in $\partial\mathbf{Y}_0$. Further, each $\mathcal{M}_i$ is isolated in $\mathbf{Y}$ and $\mathcal{W}^s(\mathcal{M}_i)\cap \mathbf{Y}_{0} = \emptyset$, where $\mathcal{W}^{s}(\mathcal{M}_i)$ is the stable set of $\mathcal{M}_i$ (see [21]). It is easy to see that no subsets of $\mathcal{M}_0$, $\mathcal{M}_1$, and $\mathcal{M}_2$ forms a cycle in $\partial\mathbf{Y}_0$. By [21,Theorem 1.3.1] on strong repellers, $\Psi(t):\mathbf{Y}\rightarrow\mathbf{Y}$ is uniformly persistent with respect to $(\mathbf{Y}_0, \partial\mathbf{Y}_0)$. It follows from [21,Theorem 1.3.6] that there exists a global attractor $\hat{\mathcal{A}}_0$ for $\Psi(t)$ in $\mathbf{Y}_0$ and $\Psi(t)$ has at least one fixed point

    $ (\tilde{R}, \tilde{S}, \tilde{Q}_1, \tilde{u}_1, \tilde{Q}_2, \tilde{u}_2)\in \mathbf{Y}_0. $

    Thus, $(\tilde{R}, \tilde{S}, \tilde{Q}_1, \tilde{u}_1, \tilde{Q}_2, \tilde{u}_2)$ is a positive steady-state solution for system (1.1). This completes the proof.

    In this paper, we study the chemostat-type system (1.1) modeling the interactions of two species competing for "CO2" (dissolved CO2 and carbonic acid), "CARB" (bicarbonate and carbonate ions), and light in a spatially homogeneous water column. Our mathematical model presented in this paper is inspired by the recent works [17,20]. In fact, system (1.1) is a modified version of the model in the Supplementary Information of [20], where the specific growth rate of the competing species $i$ depends on their stored cellular carbon content (quota) $Q_i$. The dynamics of $Q_i$ can be affected by the uptake rates of inorganic carbon, "CO2" ($R(t)$) and "CARB" ($S(t)$), photosynthetic activity ($g_i(u_1, u_2)$), and respiration ($\gamma_i(Q_i)$). The resources "CO2" and "CARB" are substitutable in their effects on algal growth, which also involves a very complex processes. In order to make our system (1.1) analytically tractable, we have adopted the ideas in [17] to assume that carbonic acid loses a proton to become bicarbonate at the rate $\omega_r$, and the rate of the reverse reaction is denoted by $\omega_s$, which simplifies the complex processes of "CO2" and "CARB" involved.

    Solutions of both the two-species system (1.1) and its single-species sub-system (2.1) follow mass conservation laws, and are eventually bounded (see Lemma 2.1 and Lemma 3.1). Persistence of a single species depends on the sign of $\mu(Q^{*})-D$ (see Theorem 2.4), where $Q^{*}$ is given in (2.8). Biologically, $Q^*$ represents the quota that a species can obtain when the inorganic carbon concentration is at its long-term upper bound $(R^{*}, S^{*})$, which is the unique equilibrium for system (2.7) governing the available inorganic carbon in a species-free habitat. Then Theorem 2.4 states that the species can persist if the quota $Q^{*}$ exceeds the quota $\hat{Q}$ required for growth to balance losses (i.e., $\mu(\hat{Q}) = D$). Thus, the persistence criterion (i.e., $\mu(Q^{*})-D>0$) summarizes the characteristics of carbon uptake, the growth rate, light availability, and the respiration rate. If the quota $Q^{*}$ is less than the quota $\hat{Q}$, then we can show that the species population is washed out of the habitat (see Theorem 2.5), where we have ignored the effect of respiration (see the specific assumption (2.11)), due to a technical reason.

    In Theorem 2.4, we only show that the single-species model (2.1) admits at least one positive equilibrium if the species can persist by using the theory of uniform persistence. The uniqueness and global stability of positive equilibrium for (2.1) are still open if no extra assumptions are imposed. Thus, two semi-trivial steady-state solutions of the two-species system (1.1), corresponds to the presence of one of the species and the absence of the other species, are not necessarily unique. This makes the investigation of coexistence for the two-species system (1.1) more difficult. Inspired by [12,Section 4], we first define two suitable parameters, $\hat{Q}_2^{\min}$ and $\check{Q}_1^{\min}$ (see 3.3 and 3.4), then we are able to show that the compact attractor $\mathcal{M}_1$ (on the boundary $u_2 = 0$), and the compact attractor $\mathcal{M}_2$ (on the boundary $u_1 = 0$) are uniform weak repellers for two-species system (1.1) (see Lemma 3.3 and Lemma 3.4) under appropriate conditions depending on $\hat{Q}_2^{\min}$ and $\check{Q}_1^{\min}$, respectively. Finally, we are able to show that system (1.1) is uniformly persistent, and it admits at least one coexistence (componentwise positive) steady-state solution (see Theorem 3.5) when the trivial steady-state solution, the compact set $\mathcal{M}_1$, and the compact set $\mathcal{M}_2$ are all invasible. From biological viewpoints, invasibility will depend on whether the missing competitor obtains sufficiently large quotas ($\hat{Q}_2^{\min}$ or $\check{Q}_1^{\min}$) to permit a growth rate that exceeds the loss to dilution ($D$). Then robust coexistence occurs when there is mutual invasibility of both $\mathcal{M}_1$ and $\mathcal{M}_2$.

    Research of F.-B. Wang is supported in part by Ministry of Science and Technology, Taiwan; and National Center for Theoretical Sciences (NCTS), National Taiwan University; and Chang Gung Memorial Hospital (CRRPD3H0011, BMRPD18 and NMRPD5F0543). We would like to express our thanks to Professor Sze-Bi Hsu for the helpful discussions in this paper.

    All authors declare no conflicts of interest in this paper.

    [1] Bozell JJ, Petersen GR (2010) Technology development for the production of biobased products from biorefinery carbohydrates-the US Department of Energy's "Top 10" revisited. Green Chem 12: 539–517. doi: 10.1039/b922014c
    [2] Werpy T, Petersen G (2004) Top Value Added Chemicals from Biomass, National Renewable Energy Laboratory: Golden, CO.
    [3] Zhang D, Dumont MJ (2017) Advances in polymer precursors and bio-based polymers synthesized from 5-hydroxymethylfurfural. J Polym Sci Pol Chem 55: 1478–1492. doi: 10.1002/pola.28527
    [4] Deng J, Pan T, Xu Q, et al. (2013) Linked strategy for the production of fuels via formose reaction. Sci Rep 3: 1244. doi: 10.1038/srep01244
    [5] Rosatella AA, Simeonov SP, Frade RFM, et al. (2011) 5-Hydroxymethylfurfural (HMF) as a building block platform: Biological properties, synthesis and synthetic applications. Green Chem 13: 754–741. doi: 10.1039/c0gc00401d
    [6] Cui MS, Deng J, Li XL, et al. (2016) Production of 4-Hydroxymethylfurfural from derivatives of biomass-derived glycerol for chemicals and polymers. ACS Sustain Chem Eng 4: 1707–1714. doi: 10.1021/acssuschemeng.5b01657
    [7] van Putten RJ, van der Waal JC, de Jong ED, et al. (2013) Hydroxymethylfurfural, a versatile platform chemical made from renewable resources. Chem Rev 113: 1499–1597. doi: 10.1021/cr300182k
    [8] Yu IKM, Tsang DCW (2017) Conversion of biomass to hydroxymethylfurfural: A review of catalytic systems and underlying mechanisms. Bioresource Technol 238: 716–732. doi: 10.1016/j.biortech.2017.04.026
    [9] Qin YZ, Zong MH, Lou WY, et al. (2016) Biocatalytic upgrading of 5-Hydroxymethylfurfural (HMF) with levulinic acid to HMF levulinate in biomass-derived solvents. ACS Sustain Chem Eng 4: 4050–4054. doi: 10.1021/acssuschemeng.6b00996
    [10] Bohre A, Dutta S, Saha B, et al. (2015) Upgrading furfurals to drop-in biofuels: An overview. ACS Sustain Chem Eng 3: 1263–1277. doi: 10.1021/acssuschemeng.5b00271
    [11] Caes BR, Teixeira RE, Knapp KG, et al. (2015) Biomass to furanics: Renewable routes to chemicals and fuels. ACS Sustain Chem Eng 3: 2591–2605. doi: 10.1021/acssuschemeng.5b00473
    [12] Alexandrino K, Millera Á, Bilbao R, et al. (2014) Interaction between 2,5-dimethylfuran and nitric oxide: Experimental and modeling study. Energ Fuel 28: 4193–4198. doi: 10.1021/ef5005573
    [13] Zhong S, Daniel R, Xu H, et al. (2010) Combustion and emissions of 2,5-dimethylfuran in a direct-injection spark-ignition engine. Energ Fuel 24: 2891–2899. doi: 10.1021/ef901575a
    [14] Ray P, Smith C, Simon G, et al. (2017) Renewable green platform chemicals for polymers. Molecules 12: 376.
    [15] Burgess SK, Leisen JE, Kraftschik BE, et al. (2014) Chain mobility, thermal, and mechanical properties of poly(ethylene furanoate) compared to poly(ethylene terephthalate). Macromolecules 47: 1383–1391. doi: 10.1021/ma5000199
    [16] Papageorgiou GZ, Tsanaktsis V, Bikiaris DN (2014) Synthesis of poly(ethylene furandicarboxylate) polyester using monomers derived from renewable resources: thermal behavior comparison with PET and PEN. Phys Chem Chem Phys 16: 7946–7958. doi: 10.1039/C4CP00518J
    [17] Codou A, Moncel M, van Berkel JG, et al. (2016) Glass transition dynamics and cooperativity length of poly(ethylene 2,5-furandicarboxylate) compared to poly(ethylene terephthalate). Phys Chem Chem Phys 18: 16647–16658. doi: 10.1039/C6CP01227B
    [18] Dimitriadis T, Bikiaris DN, Papageorgiou GZ, et al. (2016) Molecular dynamics of poly(ethylene-2,5-furanoate) (PEF) as a function of the degree of crystallinity by dielectric spectroscopy and calorimetry. Macromol Chem Phys 217: 2056–2062. doi: 10.1002/macp.201600278
    [19] Lomelí-Rodríguez M, Martín-Molina M, Jiménez-Pardo M, et al. (2016) Synthesis and kinetic modeling of biomass-derived renewable polyesters. J Polym Sci Pol Chem 54: 2876–2887. doi: 10.1002/pola.28173
    [20] Terzopoulou Z, Tsanaktsis V, Nerantzaki M, et al. (2016) Thermal degradation of biobased polyesters: Kinetics and decomposition mechanism of polyesters from 2,5-furandicarboxylic acid and long-chain aliphatic diols. J Anal Appl Pyrol 117: 162–175. doi: 10.1016/j.jaap.2015.11.016
    [21] Baba Y, Hirukawa N, Tanohira N, et al. (2003) Structure-based design of a highly selective catalytic site-directed inhibitor of Ser/Thr protein phosphatase 2B (Calcineurin). J Am Chem Soc 125: 9740–9749. doi: 10.1021/ja034694y
    [22] Clark DE, Clark KL, Coleman RA, et al. (2005) Patent No. WO2004067524.
    [23] Ermakov S, Beletskii A, Eismont O, et al. (2015) Brief review of liquid crystals, In: Liquid Crystals in Biotribology, Springer, 37–56.
    [24] Dewar MJS, Riddle RM (1975) Factors influencing the stabilities of nematic liquid crystals. J Am Chem Soc 97: 6658–6662. doi: 10.1021/ja00856a010
    [25] Kowalski S, Lukasiewicz M, Duda-Chodak A, et al. (2013) 5-hydroxymethyl-2-furfural (HMF)-heat-induced formation, occurrence in food and biotransformation-a review. Pol J Food Nutr Sci 63: 207–225.
    [26] Murkovic M, Bornik MA (2007) Formation of 5-hydroxymethyl-2-furfural (HMF) and 5-hydroxymethyl-2-furoic acid during roasting of coffee. Mol Nutr Food Res 51: 390–394. doi: 10.1002/mnfr.200600251
    [27] Murkovic M, Pichler N (2006) Analysis of 5-hydroxymethylfurfual in coffee, dried fruits and urine. Mol Nutr Food Res 50: 842–846. doi: 10.1002/mnfr.200500262
    [28] Saha B, Abu-Omar MM (2014) Advances in 5-hydroxymethylfurfural production from biomass in biphasic solvents. Green Chem 16: 24–38. doi: 10.1039/C3GC41324A
    [29] Rout PK, Nannaware AD, Prakash O, et al. (2016) Synthesis of hydroxymethylfurfural from cellulose using green processes: A promising biochemical and biofuel feedstock. Chem Eng Sci 142: 318–346. doi: 10.1016/j.ces.2015.12.002
    [30] Mukherjee A, Dumont MJ, Raghavan V (2015) Review: Sustainable production of hydroxymethylfurfural and levulinic acid: Challenges and opportunities. Biomass Bioenerg 72: 143–183. doi: 10.1016/j.biombioe.2014.11.007
    [31] Thiyagarajan S, Pukin A, van Haveren J, et al. (2013) Concurrent formation of furan-2,5- and furan-2,4-dicarboxylic acid: unexpected aspects of the Henkel reaction. RSC Adv 3: 15678–15686. doi: 10.1039/C3RA42457J
    [32] Corre C, Song L, O'Rourke S, et al. (2008) 2-Alkyl-4-hydroxymethylfuran-3-carboxylic acids, antibiotic production inducers discovered by Streptomyces coelicolor genome mining. Proc Natl Acad Sci USA 105: 17510–17515. doi: 10.1073/pnas.0805530105
    [33] Sidda JD, Corre C (2012) Gamma-butyrolactone and furan signaling systems in Streptomyces. Method Enzymol 517: 71–87. doi: 10.1016/B978-0-12-404634-4.00004-8
    [34] Wang Y, Jones MK, Xu H, et al. (2015) Mechanism of the enzymatic synthesis of 4-(Hydroxymethyl)-2-furancarboxaldehyde-phosphate (4-HFC-P) from Glyceraldehyde-3-phosphate catalyzed by 4-HFC-P synthase. Biochemistry 54: 2997–3008. doi: 10.1021/acs.biochem.5b00176
    [35] Miller D, Wang Y, Xu H, et al. (2014) Biosynthesis of the 5-(Aminomethyl)-3-furanmethanol moiety of methanofuran. Biochemistry 53: 4635–4647. doi: 10.1021/bi500615p
    [36] Wang Y, Xu H, Jones MK, et al. (2015) Identification of the final two genes functioning in methanofuran biosynthesis in Methanocaldococcus jannaschii. J Bacteriol 197: 2850–2858. doi: 10.1128/JB.00401-15
    [37] Jia J, Schorken U, Lindqvist Y, et al. (1997) Crystal structure of the reduced Schiff-base intermediate complex of transaldolase B from Escherichia coli: mechanistic implications for class I aldolases. Protein Sci 6: 119–124.
    [38] Hester G, Brenner-Holzach O, Rossi FA, et al. (1991) The crystal structure of fructose-1,6-bisphosphate aldolase from Drosophila melanogaster at 2.5 A resolution. FEBS Lett 292: 237–242. doi: 10.1016/0014-5793(91)80875-4
    [39] Sygusch J, Beaudry D, Allaire M (1987) Molecular architecture of rabbit skeletal muscle aldolase at 2.7-A resolution. Proc Natl Acad Sci USA 84: 7846–7850. doi: 10.1073/pnas.84.22.7846
    [40] Blom N, Sygusch J (1997) Product binding and role of the C-terminal region in class I D-fructose 1,6-bisphosphate aldolase. Nat Struct Biol 4: 36–39. doi: 10.1038/nsb0197-36
    [41] Izard T, Lawrence MC, Malby RL, et al. (1994) The three-dimensional structure of N-acetylneuraminate lyase from Escherichia coli. Structure 2: 361–369. doi: 10.1016/S0969-2126(00)00038-1
    [42] Kim CG, Yu TW, Fryhle CB, et al. (1998) 3-Amino-5-hydroxybenzoic acid synthase, the terminal enzyme in the formation of the precursor of mC7N units in rifamycin and related antibiotics. J Biol Chem 273: 6030–6040. doi: 10.1074/jbc.273.11.6030
    [43] Kim H, Certa U, Dobeli H, et al. (1998) Crystal structure of fructose-1,6-bisphosphate aldolase from the human malaria parasite Plasmodium falciparum. Biochemistry 37: 4388–4396. doi: 10.1021/bi972233h
    [44] Bobik TA, Morales EJ, Shin A, et al. (2014) Structure of the methanofuran/methanopterin-biosynthetic enzyme MJ1099 from Methanocaldococcus jannaschii. Acta Crystallogr F 70: 1472–1479. doi: 10.1107/S2053230X1402130X
    [45] Heine A, DeSantis G, Luz JG, et al. (2001) Observation of covalent intermediates in an enzyme mechanism at atomic resolution. Science 294: 369–374. doi: 10.1126/science.1063601
    [46] Almeida JRM, Röder A, Modig T, et al. (2008) NADH- vs NADPH-coupled reduction of 5-hydroxymethyl furfural (HMF) and its implications on product distribution in Saccharomyces cerevisiae. Appl Microbiol Biot 78: 939–945. doi: 10.1007/s00253-008-1364-y
    [47] Palmqvist E, Hahn-Hägerdal B (2000) Fermentation of lignocellulosic hydrolysates. II: inhibitors and mechanisms of inhibition. Bioresource Technol 74: 25–33.
    [48] Modig T, Lidén G, Taherzadeh MJ (2002) Inhibition effects of furfural on alcohol dehydrogenase, aldehyde dehydrogenase and pyruvate dehydrogenase. Biochem J 363: 769–776. doi: 10.1042/bj3630769
    [49] Barciszewski J, Siboska GE, Pedersen BO, et al. (1997) A mechanism for the in vivo formation of N6-furfuryladenine, kinetin, as a secondary oxidative damage product of DNA. FEBS Lett 414: 457–460. doi: 10.1016/S0014-5793(97)01037-5
    [50] Horváth IS, Taherzadeh MJ, Niklasson C, et al. (2001) Effects of furfural on anaerobic continuous cultivation of Saccharomyces cerevisiae. Biotechnol Bioeng 75: 540–549. doi: 10.1002/bit.10090
    [51] Palmqvist E, Hahn-Hägerdal B (2000) Fermentation of lignocellulosic hydrolysates. I: inhibition and detoxification. Bioresource Technol 74: 17–24.
    [52] Nicolaou SA, Gaida SM, Papoutsakis ET (2010) A comparative view of metabolite and substrate stress and tolerance in microbial bioprocessing From biofuels and chemicals, to biocatalysis and bioremediation. Metab Eng 12: 307–331. doi: 10.1016/j.ymben.2010.03.004
    [53] Wang X, Miller EN, Yomano LP, et al. (2011) Increased furfural tolerance due to overexpression of NADH-dependent oxidoreductase FucO in Escherichia coli strains engineered for the production of ethanol and lactate. Appl Environ Microb 77: 5132–5140. doi: 10.1128/AEM.05008-11
    [54] Liu ZL, Blaschek HP (2010) Biomass conversion inhibitors andin situ detoxification, In: Biomass to Biofuels: Strategies for Global Industries, Blackwell Publishing Ltd., 233–259.
    [55] Liu ZL, Moon J, Andersh BJ, et al. (2008) Multiple gene-mediated NAD(P)H-dependent aldehyde reduction is a mechanism of in situ detoxification of furfural and 5-hydroxymethylfurfural by Saccharomyces cerevisiae. Appl Microbiol Biot 81: 743–753. doi: 10.1007/s00253-008-1702-0
    [56] Nieves LM, Panyon LA, Wang X (2015) Engineering sugar utilization and microbial tolerance toward lignocellulose conversion. Front Bioeng Biotechnol 3: 1–10.
    [57] Wierckx N, Koopman F, Ruijssenaars HJ, et al. (2011) Microbial degradation of furanic compounds: biochemistry, genetics, and impact. Appl Microbiol Biot 92: 1095–1105. doi: 10.1007/s00253-011-3632-5
    [58] Zhang J, Zhu Z, Wang X, et al. (2010) Biodetoxification of toxins generated from lignocellulose pretreatment using a newly isolated fungus, Amorphotheca resinae ZN1, and the consequent ethanol fermentation. Biotechnol Biofuels 3: 26. doi: 10.1186/1754-6834-3-26
    [59] Trifonova R, Postma J, Ketelaars JJMH, et al. (2008) Thermally treated grass fibers as colonizable substrate for beneficial bacterial inoculum. Microbial Ecol 56: 561–571. doi: 10.1007/s00248-008-9376-9
    [60] López MJ, Nichols NN, Dien BS, et al. (2004) Isolation of microorganisms for biological detoxification of lignocellulosic hydrolysates. Appl Microbiol Biot 64: 125–131. doi: 10.1007/s00253-003-1401-9
    [61] Boopathy R, Daniels L (1991) Isolation and characterization of a furfural degrading sulfate-reducing bacterium from an anaerobic digester. Curr Microbiol 23: 327–332. doi: 10.1007/BF02104134
    [62] Brune G, Schoberth SM, Sahm H (1983) Growth of a strictly anaerobic bacterium on furfural (2-furaldehyde). Appl Environ Microb 46: 1187–1192.
    [63] Koopman F, Wierckx N, de Winde JH, et al. (2010) Identification and characterization of the furfural and 5-(hydroxymethyl)furfural degradation pathways of Cupriavidus basilensis HMF14. Proc Natl Acad Sci USA 107: 4919–4924. doi: 10.1073/pnas.0913039107
    [64] Dijkman WP, Groothuis DE, Fraaije MW (2014) Enzyme-catalyzed oxidation of 5-hydroxymethylfurfural to furan-2,5-dicarboxylic acid. Angew Chem Int Edit 53: 6515–6518. doi: 10.1002/anie.201402904
    [65] Dijkman WP, Fraaije MW (2014) Discovery and characterization of a 5-Hydroxymethylfurfural oxidase from Methylovorus sp. strain MP688. Appl Environ Microb 80: 1082–1090. doi: 10.1128/AEM.03740-13
    [66] Dijkman WP, Binda C, Fraaije MW, et al. (2015) Structure-based enzyme tailoring of 5-hydroxymethylfurfural oxidase. ACS Catal 5: 1833–1839. doi: 10.1021/acscatal.5b00031
    [67] de Jong E, Dam MA, Sipos L, et al. (2012) Furandicarboxylic acid (fdca), a versatile building block for a very interesting class of polyesters, In: Biobased Monomers, Polymers, and Materials, American Chemical Society, 1–13.
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